MachineLearningNotebooks/how-to-use-azureml/deploy-to-cloud

Model Deployment with Azure ML service

You can use Azure Machine Learning to package, debug, validate and deploy inference containers to a variety of compute targets. This process is known as "MLOps" (ML operationalization). For more information please check out this article: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-deploy-and-where

Get Started

To begin, you will need an ML workspace. For more information please check out this article: https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-manage-workspace

Deploy to the cloud

You can deploy to the cloud using the Azure ML CLI or the Azure ML SDK.

• CLI example: https://aka.ms/azmlcli
• Notebook example: model-register-and-deploy.